MarDini is a video diffusion model launched by Meta AI Research, integrating the advantages of Masked Auto-Regressive (MAR) within a unified Diffusion Model (DM) framework. This model enables video generation at any frame position based on any number of masked frames, supporting various video generation tasks such as video interpolation, image-to-video generation, and video extension. MarDini is designed to allocate most computational resources to a low-resolution planning model, making large-scale space-time attention feasible. MarDini sets new benchmarks in video interpolation and efficiently generates videos comparable to more costly advanced image-to-video models within a few inference steps.